The proliferation of available streaming content is increasing at exponential levels that will soon reach many millions if not billions of such viewable streaming content. Conventionally, broadcast media has been delivered by television or cable channels that typically have been associated with a relatively small number of content providers. However, with the ubiquitous nature of media creation and publishing tools, individuals are able to become prolific content creators. This has resulted in exponential growth of available streaming media content.
In order to generate information about media content, such as information that facilitates searching for the media content and receiving applications related to unique features of respective media content, the media content generally needs to be analyzed at a content level. Manual analysis of media content is highly inefficient considering the large corpus of available media content. Current automated video analysis techniques provide some relief. For example, some automated video content analysis techniques observe patterns in object movement and employ visual image recognition techniques to discern activity occurring in respective frames of a video. However, with respect to detecting points in a video where scene breaks occur, these automated video analysis techniques suffer from lack of accuracy and efficiency.